Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/waterplanai/agentic-config/ac-qa-e2e-templatenpx skills add WaterplanAI/agentic-config --skill ac-qa-e2e-templategit clone --depth 1 https://github.com/WaterplanAI/agentic-configWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/waterplanai/agentic-config/ac-qa-e2e-template)<a href="https://agentmods.dev/skills/waterplanai/agentic-config/ac-qa-e2e-template"><img src="https://agentmods.dev/badge/skills/waterplanai/agentic-config/ac-qa-e2e-template.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00046 | $0.00432 |
| Opus 5 | $0.00023 | $0.00216 |
| Sonnet 5 | $0.00009 | $0.00086 |
| Haiku 4.5 | $0.00005 | $0.00043 |
Grade A, and why
ac-qa-e2e-template scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
E2E Test:
User Story
As a I want to So that
Pre-Conditions
- Application is running at base URL
Test Steps
- Navigate to
<path> - Verify page title contains ""
- Screenshot "initial_state"
- Click ""
- Verify ""
- Type "" into ""
- Screenshot "after_action"
- Verify
Success Criteria
- Page loads without errors
- <specific criterion 1>
- <specific criterion 2>
- All screenshots captured successfully
Expected Output
{
"test_name": "<Test Name>",
"status": "passed",
"screenshots": [
"{PROJECT_ROOT}/outputs/e2e/<test-name>/01_initial_state.png",
"{PROJECT_ROOT}/outputs/e2e/<test-name>/02_after_action.png"
],
"error": null
}
Notes
- Video recording is explicit: use
playwright-cli video-startbefore andvideo-stopafter the test flow. Output saved to{PROJECT_ROOT}/outputs/e2e/ - Screenshots saved to
{PROJECT_ROOT}/outputs/e2e/<test-name>/ - Use descriptive screenshot names for clarity
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 66 lines · 46 tokens per session scan A 7fc4bdcf9247
ac-qa-e2e-template is a skill published in the GitHub repository WaterplanAI/agentic-config (30 stars, last pushed 1mo ago), licensed MIT. It adds 46 tokens to every session and 432 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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